화학공학소재연구정보센터
학회 한국화학공학회
학술대회 2018년 봄 (04/25 ~ 04/27, 창원컨벤션센터)
권호 24권 1호, p.131
발표분야 공정시스템
제목 Ensemble learning based latent variable model predictive control for batch trajectory tracking under concept drift
초록 For tracking a reference trajectory varying batch-wisely, several latent variable based model predictive controllers have been proposed and applied to the batch operation systems. In a concept drift condition, however, maintaining a single model can decrease the control performance. To solve this problem, we propose to combine an ensemble learning method with the latent variable model predictive control. By using total pool of local functions and historical data set which evolves through the process and learning weights by ensemble algorithm, the effects of concept drift on the process are reflected better to the ensemble latent variable model than the conventional method. Simulation results show that both of predictive and control performances by the proposed method are better than the ones of the conventional latent variable model predictive controller.
저자 정동휘1, 이종민2
소속 1고려대, 2서울대
키워드 화학 및 생물공정; 공정제어
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